608 Timing of Nanocrystalline Silver-based Dressing Application – a Retrospective Single-center Pediatric Cohort Study
Bibliographic record
Abstract
Abstract Introduction Nanocrystalline silver-based dressings (NSBD) are commonly used at different stages of the treatment of burn wounds. They have been shown to reduce the incidence of surgical procedures, time to re-epithelialization in partial thickness burn injuries, and decrease pain with dressing changes compared to silver sulfadiazine in adult and pediatric populations. Recent evidence has demonstrated anti-inflammatory properties in addition to the known antimicrobial properties. We hypothesized that the timing of nanocrystalline silver-based dressings application ( < 24h after burn injury) may impact surgical treatment rates. Methods This study was a retrospective single-center cohort study. All pediatric patients ( < 18 years old) treated at a single academic pediatric center for acute partial thickness burn injuries, between January 1, 2020 and December 31, 2021 were included. Bivariate analysis and multivariable logistic regression were used to compare timing of nanocrystalline silver application and surgical treatment rates. Results Four hundred seventy-six patients were included for analysis. One hundred four (21.85%) had NSBD and 372 (78.11%) had non-silver non-adherent dressings applied within the first 24 hours post injury. No statistically significant difference was found in surgical treatment, age, sex, mechanism, anatomic location, or total body surface area (TBSA) on bivariate analysis. The multivariable logistic regression identified three statistically significant variables as predictors for surgical treatment: age (OR = 1.14, 95% CI [1.06-1.23]), TBSA (OR = 1.15, 95% CI [1.06-1.25]), and burns to buttocks/lower extremity burns (excluding feet) (OR = 2.39, 95% CI [1.26-4.53]). Immediate ( < 24h) application of NSBD has not been demonstrated to decrease the likelihood of surgical treatment. Conclusions Immediate ( < 24h) application of nanocrystalline silver-based dressings does not affect surgical treatment rates. Prospective randomized studies are required to investigate the potential anti-inflammatory benefits of early nanocrystalline silver-based dressings in the treatment of pediatric burn injuries. Applicability of Research to Practice Use of nanocrystalline silver should be recommended as per clinical indications.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".